Mercurial > hg > Members > atton > intelligence_robotics
changeset 8:3325edf9139f
Mini fixes
| author | atton |
|---|---|
| date | Wed, 24 Jun 2015 15:48:35 +0900 |
| parents | 8fd9385f952b |
| children | 8a6f547b72c0 |
| files | slide.md |
| diffstat | 1 files changed, 3 insertions(+), 3 deletions(-) [+] |
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--- a/slide.md Wed Jun 24 15:21:19 2015 +0900 +++ b/slide.md Wed Jun 24 15:48:35 2015 +0900 @@ -1,4 +1,4 @@ -title: A Novel Greeting System Selection System for a Culture-Adaptive Humanoid Robot +title: A Novel Greeting Selection System for a Culture-Adaptive Humanoid Robot author: Tatsuki KANAGAWA <br> Yasutaka HIGA profile: Concurrency Reliance Lab lang: Japanese @@ -117,7 +117,7 @@ <img src="pictures/model_overview.png" style='width: 75%; margin-left: 120px;'> # Greeting selection system training data -* Mappings can be trained to an initial state with data taken from the literature of sociology studies. +* Mappings can be trained to an initial state with data taken from the literature of sociology studies. * Training data should be classified through some machine learning method or formula. * We decided to use conditional probabilities: in particular the Naive Bayes formula to map data. * Naive Bayes only requires a small amount of training data. @@ -137,7 +137,7 @@ * The mapping is represented by a dataset, initially built from training data, as a table containing weights for each context vector corresponding to each greeting type. * We now need to update these weights. -# feedback from three questionnaires +# feedback from three questionnaires <!-- FIXME : redundancy --> * Whenever a new feature vector is given as an input, it is checked to see whether it is already contained in the dataset or not. * In the former case, the weights are directly read from the dataset * in the latter case, they get assigned the values of probabilities calculated through the Naive Bayes classifier.